Bluetooth Beacon-Based Underground Navigation System to Support Mine Haulage Operations

minerals

Article BBUNS: Bluetooth Beacon-Based Underground Navigation System to Support Mine Haulage Operations

Jieun Baek 1, Yosoon Choi 1,* ID , Chaeyoung Lee 1, Jangwon Suh 2 ID and Sangho Lee 3

1 Department of Energy Resources Engineering, Pukyong National University, Busan 48513, Korea; [email protected] (J.B.); [email protected] (C.L.) 2 Energy Resources Institute, Pukyong National University, Busan 48513, Korea; [email protected] 3 Korea Institute of Geoscience and Mineral Resources, Daejeon 34132, Korea; [email protected] * Correspondence: [email protected]; Tel.: +82-51-629-6562

Received: 28 September 2017; Accepted: 18 November 2017; Published: 21 November 2017

Abstract: A Bluetooth beacon-based underground navigation system (BBUNS) was developed to identify the optimal haul road in an underground mine, track the locations of dump trucks, and display this information on mobile devices. A three-dimensional (3-D) geographic information system (GIS) database of the haul roads in an underground mine was constructed, and the travel time for each section was calculated. A GIS database was also constructed for 50 Bluetooth beacons that were installed along the haul roads. An Android-based BBUNS application was developed to visualize the current location of each dump truck and the optimal haul road to the destination on mobile devices, using the Bluetooth beacon system that was installed in the underground mine. Whenever the BBUNS recognized all of the Bluetooth beacons installed in the underground mine, it could provide the dump truck drivers with information on the current location and the two-dimensional (2-D) and 3-D haul road properties. The operating time of each dump truck and the time spent on each unit task could be analyzed using recorded data on the times when Bluetooth beacon signals were recognized by the BBUNS. The underground mine navigation system that was developed in this study can contribute to the improvement of haul operation efﬁciency and productivity.

Keywords: underground mine; navigation system; Bluetooth beacon system; truck haul operations

1. Introduction All over the world, as high-quality ore deposits near ground surfaces have been extensively mined and are now almost exhausted, the mining industry is increasingly using large machines to mine low-quality ore deposits at greater depths at mining sites. At highly mechanized mining sites, the efficient operation and management of equipment are crucial not only for productivity and safety during mining work, but also for the profitability of mining corporations. Various types of fleet management systems (FMSs) have been developed at mining sites for the efficient operation and management of mining equipment [1–4]. The key technologies that are provided by FMSs in relation to loading and haul operations at mining sites include dispatching technology [1,5–18] that identifies optimal combinations of equipment and adjusts dispatch intervals, routing technology [19–22] that identifies optimal equipment travel routes, and tracking technology [23] that monitors the current location and operational status of each piece of equipment. FMSs include navigation systems that identify the optimal haul road to the destination, track the location of each piece of transport equipment at a mining site, and display information, such as the optimal haul road, the current location of the equipment, and the cycle time, on a device that is mounted in each vehicle. The navigation systems have been introduced recently at mining sites

Minerals 2017, 7, 228; doi:10.3390/min7110228 www.mdpi.com/journal/minerals Minerals 2017, 7, 228 2 of 16 as new solutions for maximizing the efficiency or haul operations. For instance, Hexagon Mining’s Jtruck (2017, Brisbane, QLD, Australia) [24], which is a typical navigation system for use in open-pit mines, updates haul vehicle dispatch information and haul road information in real time through a wireless communication infrastructure and tracks the current location of each dump truck using global positioning system (GPS) signals. In addition, terminals are installed in each vehicle to provide the driver with real-time information on the current location of the vehicle in the mine and the distance along the haul road to the destination. In underground mines, however, it is difficult to share haul operation information with people outside of the mine and to track the location of the equipment in real time, because the haul operations are conducted with disconnected GPS signals and wired/wireless communication [25]. The development of a navigation system for underground mines requires three types of techniques. The first technique can determine the optimal haul road from a certain departure location to a workplace destination for haul operations. Geographic Information System (GIS)-based network analysis is a typical technique that is used to analyze the travel routes that connect a departure point and destination point and then identify the optimal travel route—i.e., the one with the lowest travel cost—in an environment in which vector networks such as roads, railways, and waterways are constructed [22,26–28]. The travel cost factors that are considered when analyzing the optimal travel route include distance, time, speed, terrain slope, resistance, and other factors that are related to various phenomena that may occur in a network environment [29–33]. Several studies have been conducted using the GIS-based network analysis technique to identify the optimal travel route and minimize the haul operation time of load–haul–dump (LHD) equipment in underground mine environments [6,19,20,34]. The second type of technique that is required for a navigation system for underground mines is one that can recognize the exact location of each dump truck using wireless sensor technologies. Recent installations of wireless sensor networks [35,36], Wi-Fi [37,38], Zigbee [25,39], and radio frequency identification (RFID) tags [40–42] in underground mines have made it possible to track transport equipment and communicate between the inside and the outside of underground mines. In addition, various mining corporations have commercialized products for use in accurately locating and tracking transport and loading equipment in underground mines. Among these products are Minetec’s Trax+Tags TM II (2017, Perth, WA, Australia) [43], which uses a wireless ad hoc system; Modular Mining Systems’ Dispatch (2017, Tucson, AZ, USA) [44]; and Mine Site Technologies’ Asset tracking system (2017, Sydney, NSW, Australia) [45], which uses RFID tag technology. Technologies that can be used to recognize the location of individual dump trucks and measure travel times using a Bluetooth beacon system have attracted attention recently [46,47]. Bluetooth beacon systems are based on Bluetooth low-energy (BLE) technology, which is part of Bluetooth 4.0 wireless technology, and is mainly used for indoor positioning using smart devices [48]. BLE technology is designed to operate for many years with lower power consumption than the existing Bluetooth technologies, and the reduced packet size enables efficient data transmission [49]. A comparison between BLE and other communication technologies, such as reverse RFID for mining applications can be found in Baek et al. [50]. The third requirement is a technique that displays the current location of each dump truck in the underground mine, along with the travel route to the destination. Terminal-type products that display the current location of each dump truck in an underground mine have recently been commercialized. For example, Maptek’s MineSuite Fleet management system (2017, Denver, CO, USA) [51] identifies the location of each dump truck in an underground fleet using an RFID system that is installed in the underground mine and displays each location on terminals. MISOM Technologies’ FARA application (2017, Tucson, AZ, USA) [46] recognizes the location of each dump truck using a Bluetooth beacon system in an underground mine and displays the current location and distance to the destination on mobile devices. Mobile applications can be implemented on various smart devices, such as tablets, and the acquired data can be shared outside the mine through wireless communications technology. Minerals 2017, 7, 228 3 of 16

Minerals 2017, 7, 228 3 of 16 Nevertheless, a navigation system that combines routing, tracking, and display techniques has not beenThe developed purpose for of underground this study was mines. to develop a Bluetooth beacon-based underground navigation systemThe (BBUNS) purpose that of this could study track was the to exact develop location a Bluetooth of each beacon-baseddump truck in underground an underground navigation mine, analyzesystem (BBUNS)the optimal that haul could road track from the the exact current location loca oftion each to the dump destination, truck in anand underground display this mine,on a mobileanalyze device. the optimal For this haul purpose, road froman underground the current limestone location to mine the destination,was selected andas the display study thisarea, on a three-dimensionala mobile device. For (3-D) this GIS purpose, database an was underground constructed limestone for all of its mine haul was roads, selected and a asBluetooth the study beacon area, systema three-dimensional was installed (3-D) in the GIS underground database was mine. constructed In addition, for all a of mobile its haul application roads, and awas Bluetooth developed beacon to recognizesystem was the installed current inlocation the underground of each dump mine. truck In addition,in the underground a mobile application mine using was the developed signals that to arerecognize transmitted the current by the location Bluetooth of beacons each dump and truck to visu inalize the underground the haul road mine to the using destination. the signals The that results are oftransmitted the field application by the Bluetooth of this beaconsnavigation and system to visualize are presented. the haul road to the destination. The results of the ﬁeld application of this navigation system are presented. 2. Materials and Methods 2. Materials and Methods 2.1. Study Area 2.1. Study Area In this study, the Daesung MDI underground limestone mine (37°19′7″ N, 129°6′14″ E) in SamcheokIn this city, study, Gangwon-do, the Daesung South MDI undergroundKorea was selected limestone as minethe study (37◦19 0area700 N, (Figure 129◦60 141).00 E)This in undergroundSamcheok city, mine Gangwon-do, produces South1,500,000 Korea tons was of selected high-quality as the limestone study area every (Figure year1). Thisthrough underground the room andmine pillar produces mining 1,500,000 method. tons The of high-qualitylimestone produced limestone isevery used yearfor various through purposes, the room andsuch pillar as iron mining and cementmethod. manufacturing. The limestone produced The height is usedof the for uppermost various purposes, workplace such in as the iron underground and cement manufacturing.mine is 590 m aboveThe height sea level, of the and uppermost the depth workplace of the workplace in the underground is 170 m. mine is 590 m above sea level, and the depth of the workplace is 170 m.

Figure 1. Illustrations of the study area. The reference grid is in m. The origin of the local Transverse FigureMercator 1. Illustrations coordinate system of the isstudy 38◦00 area.00000 TheN, 127reference◦0000000 gridE (map is indatum: m. The GRS1980).origin of the local Transverse Mercator coordinate system is 38°00′00″ N, 127°00′00″ E (map datum: GRS1980). The underground mine in the study area mainly uses dump trucks for the transport of ore and The underground mine in the study area mainly uses dump trucks for the transport of ore and waste stone. The dump trucks carry the ore produced in the workplace to a crushing plant located waste stone. The dump trucks carry the ore produced in the workplace to a crushing plant located outside the underground mine and drops it into a crusher. The waste mined during ore production outside the underground mine and drops it into a crusher. The waste mined during ore production is carried by the dump trucks to a waste dump located inside the underground mine, where it is is carried by the dump trucks to a waste dump located inside the underground mine, where it is discharged. In this study, an underground mine navigation system was designed for the dump trucks discharged. In this study, an underground mine navigation system was designed for the dump trucks that carry ore while traveling between the underground mine and the crushing plant that is located that carry ore while traveling between the underground mine and the crushing plant that is located outside the underground mine. outside the underground mine. The destination of each dump truck carrying ore depends on the location of the workplace where The destination of each dump truck carrying ore depends on the location of the workplace where the limestone ore is produced. The production of limestone ore in the study area is planned on a daily the limestone ore is produced. The production of limestone ore in the study area is planned on a daily basis using a production planning system, and the location of the workplace is selected according to basis using a production planning system, and the location of the workplace is selected according to the production plan. Once the location of the workplace is determined, the task administrator provides the production plan. Once the location of the workplace is determined, the task administrator provides the drivers of the dump trucks with the location information of the workshop. If production occurs in multiple workplaces at the same time, the task administrator analyzes the dump truck

Minerals 2017, 7, 228 4 of 16 the drivers of the dump trucks with the location information of the workshop. If production occurs in multiple workplaces at the same time, the task administrator analyzes the dump truck placement and informs each driver of the location of the workshop to which he is assigned. The dump trucks travel to the assigned workshops through the haulage way that is installed inside the underground mine and carry the ore to the crushing plant that is located outside the mine. The dump trucks travel back and forth between the crushing plant and the workplace to transport the ore. Each dump truck travels 8–9 times per day on average. Currently, limestone ore in underground mines is mainly produced in 420 ML, 520 ML, and 540 ML workplaces.

2.2. Design of the Underground Mine Navigation System In this study, a BBUNS was designed for use in underground limestone mines. First, a 3-D GIS database was constructed for all of the haul roads in the underground mine to analyze the optimal haul road using a network analysis technique. Multiple Bluetooth beacons were then installed along the haul roads in the underground mine, and a location information database for the Bluetooth beacons was constructed. Finally, an Android-based underground mine navigation application was developed to detect the signals that are transmitted by the Bluetooth beacons and display the location of each dump truck and the optimal haul road on mobile devices.

2.2.1. Construction of the 3-D GIS Database The travel time of a dump truck was set as the objective function for network analysis, and the optimal haul road was deﬁned as the one that minimizes the travel time between the crushing plant and the workplace. The optimal haul road was analyzed using Dijkstra’s algorithm [31], which is a graph theory-based route optimization algorithm. Figure2 shows an example of an analysis of the travel route with the lowest travel cost on a vector network using Dijkstra’s algorithm. A vector network consists of links and nodes that are connecting the links. In all of the links, the travel cost that is required to pass through them is recorded, and, in all of the nodes, the cumulative travel cost required to travel from the departure node (n0) to the corresponding node is recorded (see Figure2a). First, the travel cost required to travel from the departure node (n0) to the neighboring nodes (n1 and n2) is calculated and is compared with the already recorded value (∞). The lower value is updated as the new cumulative travel cost (see Figure2b). After the calculation, the departure node (n0) converts to a “ﬁxed” state for which the cumulative travel cost is not changed, and node (n2) with the lowest cumulative travel cost converts to the new departure node (see Figure2c). In the same manner, the cumulative travel costs of all the nodes on the vector network are calculated (see Figure2d,e). When cumulative travel costs are provided to all of the nodes, the optimal travel route that connects the departure node (n0) and the destination node (n3) at the lowest travel cost is derived (see Figure2f). A more detailed description of the network analysis process can be found in Huang et al. [52]. To analyze the optimal haul road for the dump trucks via a network analysis, a 3-D GIS database was constructed for all of the haul roads inside the underground mine of the study area (see Figure3). The haul roads for dump trucks in the study area consists of a haul road outside the mine that connects the crushing plant and the portal of the mine, an adit that connects the portal of the mine to an intersection, declines that connect the intersection to the entrances to the levels, ramps that connect the levels, and the levels in the workplace. The declines and ramps are shafts with slopes between −8◦ and 8◦, and the rest of the haul roads are drifts with slopes of approximately 0◦. The drifts were represented as new polylines along the haul roads that are marked on the mine drawing and were digitized in a way that provides an elevation value to each polyline. The shafts and ramps were digitized by forming points corresponding to the two end points of the polyline, providing them with different elevation values, and then forming a tilted polyline connecting the two points. After combining all of the digitized haul roads into one, the haul road was divided at regular intervals of 50 m, based on the signal output range of a Bluetooth beacon. For the haul roads that are Minerals 2017, 7, 228 4 of 16 placement and informs each driver of the location of the workshop to which he is assigned. The dump trucks travel to the assigned workshops through the haulage way that is installed inside the underground mine and carry the ore to the crushing plant that is located outside the mine. The dump trucks travel back and forth between the crushing plant and the workplace to transport the ore. Each dump truck travels 8–9 times per day on average. Currently, limestone ore in underground mines is mainly produced in 420 ML, 520 ML, and 540 ML workplaces.

2.2.1. Construction of the 3-D GIS Database The travel time of a dump truck was set as the objective function for network analysis, and the optimal haul road was defined as the one that minimizes the travel time between the crushing plant and the workplace. The optimal haul road was analyzed using Dijkstra’s algorithm [31], which is a graph theory-based route optimization algorithm. Figure 2 shows an example of an analysis of the travel route with the lowest travel cost on a vector network using Dijkstra’s algorithm. A vector network consists of links and nodes that are connecting the links. In all of the links, the travel cost that is required to pass through them is recorded, and, in all of the nodes, the cumulative travel cost required to travel from the departure node (n0) to the corresponding node is recorded (see Figure 2a). First, the travel cost required to travel from the departure node (n0) to the neighboring nodes (n1 and n2) is calculated and is compared with the already recorded value (∞). The lower value is updated as the new cumulative travel cost (see Figure 2b). After the calculation, the departure node (n0) converts to a “fixed” state for which the cumulative travel cost is not changed, and node (n2) Minerals 2017, 7, 228 5 of 16 with the lowest cumulative travel cost converts to the new departure node (see Figure 2c). In the same manner,Minerals 2017 the, 7 cumulative, 228 travel costs of all the nodes on the vector network are calculated (see Figure5 of 16 2d,e). When cumulative travel costs are provided to all of the nodes, the optimal travel route that connects the departure node (n0) and the destination node (n3) at the lowest travel cost is derived (seeconstructed Figure 2f). inside A more the workplace, detailed description all of the points of the wherenetwork two analysis or more process haul roads can withbe found different in Huang travel etdirections al. [52]. cross were cut, and multiple haul roads were generated.

(d) (e) (f)

Figure 2. Example of analyzing the optimal path through a vector network using Dijkstra’s algorithm. (a) Vector network consisting of links and nodes; (b) Calculating the travel cost required to travel from n0 to n1 and n2; (c) Calculating the travel cost required to travel from n2 to n1, n3, and n4; (d) Calculating the travel cost required to travel from n4 to n3; (e) Calculating the travel cost required

Mineralsto 2017 travel, 7, 228from n1 to n3; (f) The optimal travel route that connects the departure node(n0) and the5 of 16 (a) (b) (c) destination node(n3) at the lowest travel cost.

To analyze the optimal haul road for the dump trucks via a network analysis, a 3-D GIS database was constructed for all of the haul roads inside the underground mine of the study area (see Figure 3). The haul roads for dump trucks in the study area consists of a haul road outside the mine that connects the crushing plant and the portal of the mine, an adit that connects the portal of the mine to an intersection, declines that connect the intersection to the entrances to the levels, ramps that connect the levels, and the levels in the workplace. The declines and ramps are shafts with slopes between −8° and 8°, and the rest of the haul roads are drifts with slopes of approximately 0°. The drifts were represented as new polylines along the haul roads that are marked on the mine drawing and were digitized in a way(d) that provides an elevation va(elue) to each polyline. The shafts( fand) ramps were digitized by forming points corresponding to the two end points of the polyline, providing them with FigureFigure 2. 2. ExampleExample of of analyzing analyzing the the optimal optimal path path through through a avector vector network network using using Dijkstra’s Dijkstra’s algorithm. algorithm. different((aa)) Vector Vector elevation network network values, consisting consisting and of ofthen links links forming and and nodes; nodes; a ti( (bltedb)) Calculating Calculating polyline the theconnecting travel travel cost cost the required required two points.to to travel travel After combiningfromfrom n0 n0 all to to ofn1 n1 the and and digitized n2; n2; ( (cc)) Calculating Calculating haul roads the the into travel travel one, cost cost the required required haul road to to travel travelwas dividedfrom from n2 n2 atto to regularn1, n1, n3, n3, and andintervals n4; n4; of 50 m,((d dbased)) Calculating Calculating on the the thesignal travel travel output cost cost requir required rangeed ofto to atravel travel Bluet from fromooth n4 n4 beacon. to to n3; n3; ( (e eFor)) Calculating Calculating the haul theroads the travel travel that cost cost are required required constructed insidetoto thetravel travel workplace, from from n1 n1 to to all n3; n3; of ( (fthef)) The The points optimal optimal where travel travel two route route or morethat that connects connectshaul roads the the departurewith departure different node(n0) node(n0) travel and and directions the the crossdestinationdestination were cut, node(n3) node(n3)and multiple at at the the haullowest lowest roads travel travel were cost. cost. generated.

Figure 3. Three-dimensional view of haul roads constructedconstructed in the undergroundunderground mine.mine. Haul roads consist of an adit, declines, ramps, levels,levels, andand aa haulhaul roadroad outsideoutside thethe mine.mine.

Figure 3. Three-dimensional view of haul roads constructed in the underground mine. Haul roads consist of an adit, declines, ramps, levels, and a haul road outside the mine.

Minerals 2017, 7, 228 6 of 16

The travel times required to travel along each polyline on a digitized 3-D haul road were calculated. To calculate the travel time for all of the polylines, estimates by Park et al. [34] were used for the average travel speed of a 15-ton dump truck for each type of haul road in the Daesung MDI undergroundMinerals 2017, 7, 228limestone mine (see Table 1). The time required to travel along each polyline 6was of 16 calculated by dividing the length of the polyline by the average travel speed of the dump truck, and the calculated values were assigned as attributes of the polylines. The travel times required to travel along each polyline on a digitized 3-D haul road were calculated. To calculateTable 1. theApproximate travel time speed for all and of thetravel polylines, time of a estimates 15-ton dump by Park truck et according al. [34] were to the used type for of the haul average travelroad speed in the of study a 15-ton area [34], dump where truck H denotes for each the type haul ofroad haul outside road the in un thederground Daesung mine, MDI A underground denotes limestonethe adit, mine D denotes (see Table the 1decline,). The timeR denotes required the ramp, to travel and along L denotes each the polyline level. was calculated by dividing the length of the polyline by the average travel speed of the dump truck, and the calculated values Approximate Speed (km/h) Travel Time (min) wereType assigned of asLength attributes of the polylines. Route 1—Crushing Route 2—Workplace Haul Road (m) Empty Loaded Plant to Workplace to Crushing Plant Table 1. Approximate speed and travel time of a 15-ton dump truck according to the type of haul road H 50 20 15 0.15 0.2 in the study area [34], where H denotes the haul road outside the underground mine, A denotes the A 50 20 15 0.15 0.2 adit, D denotes the decline, R denotes the ramp, and L denotes the level. D 50 10 5 0.3 0.6 R 50 10 5 0.3 0.6 Approximate Speed (km/h) Travel Time (min) L Variable 15 15 Variable Variable Type of Haul Road Length (m) Route 1—Crushing Route 2—Workplace to Empty Loaded Plant to Workplace Crushing Plant 2.2.2. InstallationH of Bluetoot 50h Beacons 20 in the Underground 15 Mine 0.15 0.2 A 50 20 15 0.15 0.2 In this Dstudy, a total of 50 50 Bluetooth 10 beacons were 5 installed in the 0.3 420 ML, 520 ML, 0.6 and 540 ML R 50 10 5 0.3 0.6 workplaces Lin the underground Variable mine 15where limestone 15 is produced Variable and along all of the Variable haul roads on which dump trucks travel in order to enter the workplaces (see Figure 4). Bluetooth beacons have advantages2.2.2. Installation for use of in Bluetooth underground Beacons mines: in the(a) they Underground offer outstanding Mine signal detection and recognition capability in extreme environments; (b) it is possible to deploy them in an easier and cheaper way than otherIn this wireless study, acommunication total of 50 Bluetooth systems, beacons becaus weree smartphones installed in can the be 420 used ML, as 520 beacon ML, recognition and 540 ML terminals;workplaces and, inthe (c) undergroundit is easy to develop mine where applicat limestoneions for is them, produced insofar and as along the Software all of the Development haul roads on Kitwhich (SDK) dump for Bluetooth trucks travel beacon in order products to enter is available the workplaces to the public (see Figure[47,53].4 ). Bluetooth beacons have advantagesFour Bluetooth for use inbeacons underground were installed mines: (a)outside they offerthe underground outstanding signal mine. detectionInside the and underground recognition mine,capability Bluetooth in extreme beacons environments; were installed (b) at itthe is possiblecenter of toeach deploy 50-m themsegment in an of easiereach haul and road. cheaper For waythe haulthan roads other wirelessinside the communication workplaces, beacons systems, were because installed smartphones on curves can with be usedbends as of beacon 90° or recognitionmore (see Figureterminals; 5). When and, (c) considering it is easy to the develop height applications of the driver for in them,the type insofar of 15-ton as the dump Software truck Development that is used Kitin the(SDK) study for area, Bluetooth the Bluetooth beacon products beacons iswere available installed to the2.5 publicm above [47 the,53 ].road surface.

(a) (b) (c)

FigureFigure 4. 4. InstallingInstalling Bluetooth Bluetooth beacons beacons (a (a) )in in the the portal portal of of the the mine mine and and (b (b) )in in the the underground underground mine; mine; ((cc)) Bluetooth Bluetooth beacon beacon with with minor minor ID ID 22. 22.

Four Bluetooth beacons were installed outside the underground mine. Inside the underground mine, Bluetooth beacons were installed at the center of each 50-m segment of each haul road. For the haul roads inside the workplaces, beacons were installed on curves with bends of 90◦ or more (see Figure5). When considering the height of the driver in the type of 15-ton dump truck that is used in the study area, the Bluetooth beacons were installed 2.5 m above the road surface. Minerals 2017,, 7,, 228228 7 of 16

Figure 5. Underground mine map showing the installation position of Bluetooth beacons. Figure 5. Underground mine map showing the installation position of Bluetooth beacons.

The beacons installed in the underground mine were RECO beacons (2017, Seoul, Korea) [54], [54], manufactured by Perples. Each RECO beacon is a terminal that periodically transmits BLE signals. The user can set the signal strength strength and signal signal tran transmissionsmission cycle cycle using using the the administrator administrator application. application. A RECORECO beaconbeacon cancan bebe operatedoperated byby Apple’sApple’s iBeaconiBeacon andand Google’sGoogle’s Eddystone,Eddystone, which are beacon standards used worldwide that are compatible with various iOS- and Android-based smart devices that support Bluetooth 4.0 technology. ThisThis equipmentequipment complies with electrical and communication standards, including the Federal CommunicationCommunication Commission (FCC), Korea Certification Certification (KC), ConformitConformitéé EuropEuropéeneéene (CE) (CE) marking, marking, and and the Technicalthe Technical Regulations Regulations Conformity Conformity Certification Certification (TELEC) for(TELEC) operations for operations in South Korean in South mines Korean [47]. They mines are considered[47]. They asare suitable considered for the as environment suitable for inside the anenvironment underground inside mine, an becauseunderground these beaconsmine, because are durable, these waterproof, beacons are and durable, relatively waterproof, insensitive and to dustrelatively [53]. Ininsensitive this study, to the dust signal [53]. intensityIn this study, of the the Bluetooth signal intensity beacons wasof the set Bluetooth to 4 dBm beacons to maximize was theset BLEto 4 dBm signal to recognition maximize the rate BLE of smart signal devices recognition inside ra thete undergroundof smart devices mine, inside and the the underground signal transmission mine, cycleand the was signal set to transmission 0.01 s. Detailed cycle specifications was set to 0.01 of the s. Detailed RECO beacons specifications are listed of inthe Table RECO2. beacons are listed in Table 2. Table 2. Specifications of the RECO beacons (Perples, Seoul, Korea) installed in the underground mine. Table 2. Specifications of the RECO beacons (Perples, Seoul, Korea) installed in the underground mine. Properties Dimensions 45Properties mm × 20 mm (Diameter × Height) DimensionsWeight 45 mm ൈ 11.620 mm g (0.4 (Diameter oz) ൈ Height) WeightProcessor 32-bit ARM® Cortex®-M0 11.6 (ARM g Holdings,(0.4 oz) Cambridge, UK) ProcessorChipset 32-bit Nordic ARM nrf51822® Cortex (Nordic®-M0 Semiconductor, (ARM Holdings, Oslo, Cambridge, Norway) UK) Battery CR2450 Lithium Coin Battery (3 V, 620 mAh, Panasonic, Osaka, Japan) ChipsetCasing Nordic Acrylonitrile nrf51822 Butadiene(Nordic Semiconductor, Styrene (ABS) Plastic Oslo, Norway) ThermalBattery Resistance CR2450 Lithium Coin Battery 93 ◦C (3 (200 V, 620◦F) mAh, Panasonic, Osaka, Japan) OperatingCasing Acrylonitrile Butadiene Styrene (ABS) Plastic −10–60 ◦C (14–140 ◦F) ThermalTemperature Resistance 93 °C (200 °F) Tx Power −16–4 dbm Operating Temperature −10–60 °C (14–140 °F) Signal range 1–70 m Tx Power −16–4 dbm Signal range 1–70 m For the efficient operation and management of the Bluetooth beacon system, a unique ID was assignedFor the to each efficient of the operation Bluetooth and beacons management that were of installedthe Bluetooth in the beacon underground system, mine. a unique iBeacon ID was can assignassigned different to each universallyof the Bluetooth unique beacons identifiers that we (UUID)re installed and majorin the underground and minor values mine. foriBeacon different can Bluetoothassign different beacons universally so that all ofunique the beacons identifiers installed (UUID) in a and certain major area and can minor be identified. values Forfor example,different

Minerals 2017, 7, 228 8 of 16 if the same UUID value is applied to all of the Bluetooth beacons installed by company A, with different major values applied according to the different installation area codes, and minor values starting from 1 are assigned to each Bluetooth beacon that is installed in the same area, all of the Bluetooth beacons can be easily identiﬁed and managed. The size of a UUID can be set up to 16 bytes, and the sizes of the major and minor values can be set up to 2 bytes. An integer between 0 and 65,535 can be assigned as a major or minor value. In this study, the same UUID and major values were applied to all of the Bluetooth beacons that were installed in the underground mine, while numbers from 1 to 50 were assigned as the minor values along the travel route of the dump trucks, as shown in Figure5.

2.2.3. Development of the Mobile Underground Mine Navigation Application A BBUNS application was developed to identify the location of each dump truck in the underground mine by analyzing the signals from the beacons and to display the locations and the optimal haul road to the destination on mobile devices. The BBUNS application was developed based on the Android operating system (Google, Menlo Park, CA, USA). Android applications can be developed easily using the Android application programming interface (API) and multiple libraries (e.g., SQLite and OpenGL), which are included in the Android software development kit (SDK) provided by Google. In addition, the key functions and development tools required to develop applications can be obtained easily, because Android provides an open-source platform. The BBUNS application was developed using Android Studio, one of the Android application development tools, and was implemented using the Java programming language. BBUNS applications can be used in various Android-based mobile devices, such as smartphones and tablets. The BBUNS application developed recognizes the minor ID of the Bluetooth beacon that transmits a signal when the dump truck enters the Bluetooth signal reception area. To accurately recognize Bluetooth beacons, the BBUNS was designed to receive wireless signals from Bluetooth beacons at one-second intervals. If different signals from two different Bluetooth beacons are received, the minor ID of the closest beacon is recognized. The signal reception area can be extended by increasing the signal output intensity of the Bluetooth beacons. As the signal intensity is set higher, however, the batteries of the Bluetooth beacons are consumed more rapidly. Therefore, the user must set reasonable signal intensity. When the BBUNS recognizes a Bluetooth beacon, it stores all of the information concerning the beacon, such as the UUID, major ID, minor ID, signal intensity, recognition time, and recognized distance, in the database. The Bluetooth beacon signal recognition function was implemented using the Reco SDK provided by Perples. The underground mine haul operation administrator analyzes the optimal haul road from the crushing area to the workplace where limestone is produced via network analysis. After the optimal haul road is identiﬁed and extracted as a new polyline, the minor IDs of all the Bluetooth beacons installed along the route are retrieved by means of a spatial query. The information about all of the minor IDs is then uploaded to a web server (see Figure6). If the location of the workplace changes, then the process described above is performed again, and all of the minor IDs retrieved along the changed travel route are uploaded again to the web server. If the BBUNS application recognizes the Bluetooth beacon with minor ID 1 installed in the crushing plant, it logs into the web server and checks whether the version of the web server has been updated. As a wireless internet environment, such as Wi-Fi, is required to access the web server, the Bluetooth beacon with minor ID 1 was installed in an outdoor environment. An update of the web server means that the workplace has been changed, and thus that the optimal haul road has changed. Therefore, the BBUNS application downloads the modiﬁed Bluetooth beacon minor information and two-dimensional (2-D) and 3-D route pictures from the web server and stores them in the database of the device. If the version of the web server has not been updated, the route pictures that are stored in the database are used. MineralsMinerals2017 2017, ,7 7,, 228 228 99 of of 16 16

Figure 6. Conceptual view of data exchanges that occur when Bluetooth beacon-based underground navigationFigure 6. Conceptual system (BBUNS) view of recognizes data exchanges the signal that of oc Bluetoothcur whenbeacon Bluetooth that beacon-based has minor ID underground 1. navigation system (BBUNS) recognizes the signal of Bluetooth beacon that has minor ID 1.

AfterAfter thethe downloaddownload ofof datadata throughthrough thethe webweb serverserver isis complete,complete, thethe BBUNSBBUNS visualizesvisualizes thethe optimaloptimal haul haul roadroad toto thethe destinationdestination throughthrough thethe graphicalgraphical useruser interfaceinterface (GUI)(GUI) ofof thethe mobilemobile device.device. TheThe BBUNS BBUNS visualizes visualizes new new 2-D 2-D and and 3-D 3-D viewsviews ofof thethe optimaloptimal haulhaul roadroad wheneverwhenever itit recognizesrecognizes newnew BluetoothBluetooth beaconsbeacons thatthat areare installedinstalled alongalong thethe haulhaul road.road. TheThe 2-D2-D picturespictures showshow aa 2-D2-D viewview ofof thethe haulhaul road road to to the the destination,destination, the the current current dump dump truck truck location, location, travel travel direction, direction, and and all all of of the theBluetooth Bluetooth beaconsbeacons alongalong thethe route.route. TheThe 3-D3-D picturespictures displaydisplay aa 3-D3-D viewview ofof thethe haulhaul roadroad fromfrom thethe pointpoint wherewhere thethe current current Bluetooth Bluetooth beacon beacon is is recognized recognized to to the the point point where where the the Bluetooth Bluetooth beacon beacon to to be be recognized recognized nextnext is is located. located. As As all all of of the the haul haul roads roads start start from from the the crushing crushing plant, plant, the the optimal optimal haul haul road road picture picture for thefor Bluetooththe Bluetooth beacon beacon with with minor minor ID 1 ID is 1 visualized is visualized ﬁrst, first, and and the the optimal optimal haul haul road road is visualized is visualized in thein the order order of theof the Bluetooth Bluetooth beacon beacon minor minor IDs IDs installed installed along along the the optimal optimal haul haul road. road. The The dump dump truck truck driverdriver travelstravels alongalong thethe routeroute displayeddisplayed onon thethe mobilemobile devicedevice toto thethe workplace,workplace, loadsloads limestonelimestone ore,ore, andand travels travels back back to to the the crushing crushing plant. plant. TheThe returnreturn route route is isvisualized visualized in in the thesame samemanner manner as asdescribed described previously.previously. As As the the BBUNS BBUNS application application does does not not require require a a separate separate wireless wireless Internet Internet environment environmentfor for visualization,visualization, it it can can be be implemented implemented in in underground underground mines mines where where a wirelessa wireless Internet Internet environment environment is notis not in place.in place. WhenWhen thethe dumpdump trucktruck arrives arrives atat the the crushing crushing plant plant again, again, the the BBUNS BBUNS recognizes recognizes the the Bluetooth Bluetooth beaconbeacon withwith minorminor IDID 1.1. AtAt thisthis time,time, thethe informationinformation forfor allall ofof thethe Bluetooth Bluetooth beaconsbeacons (e.g.,(e.g., signalsignal recognitionrecognition time,time, UUID,UUID, majormajor ID,ID, minorminor ID,ID, andand RSSI)RSSI) recognizedrecognized byby thethe applicationapplication duringduring thethe operationoperation isis uploadeduploaded toto thethe web web server server and and then then deleted deleted from from the the database. database.The The dump dump truck truck again again receivesreceives destination destination information information and and pictures pictures through through the the webweb serverserver andand repeatsrepeats thethe haulhaul operation.operation. 3. Results and Discussion 3. Results and Discussion On 15 February 2017, the location of the limestone production workplace was determined to On 15 February 2017, the location of the limestone production workplace was determined to be be 540 ML, and a total of four dump trucks were assigned to the 540 ML workplace. The crushing 540 ML, and a total of four dump trucks were assigned to the 540 ML workplace. The crushing plant plant was set as the departure point, and the loading point of the 540 ML workplace was set as the was set as the departure point, and the loading point of the 540 ML workplace was set as the destination. The optimal haul road that would minimize the truck travel time was determined via destination. The optimal haul road that would minimize the truck travel time was determined via network analysis (see Figure7a). The length of the haul road was determined to be approximately network analysis (see Figure 7a). The length of the haul road was determined to be approximately 4.56 km. As a result of the retrieval of the minor IDs of all the Bluetooth beacons that were installed 4.56 km. As a result of the retrieval of the minor IDs of all the Bluetooth beacons that were installed along the optimal haul road through a spatial query, 30 Bluetooth beacons with minor IDs 1–30 were along the optimal haul road through a spatial query, 30 Bluetooth beacons with minor IDs 1–30 were detected (see Figure7b). detected (see Figure 7b).

Minerals 2017, 7, 228 10 of 16 Minerals 2017, 7, 228 10 of 16 Minerals 2017, 7, 228 10 of 16

(a) (a)

(b) (b) Figure 7. (a) Optimal haul road connecting the crushing plant and 540 ML workplace; (b) Bluetooth Figure 7. (a) Optimal haul road connecting the crushingcrushing plant and 540 ML workplace; ( b) Bluetooth beacons that installed along the optimal haul road. beacons that installed along the optimal haul road. When the BBUNS application recognized the 30 different Bluetooth beacons, pictures showing When the BBUNS application recognized the 30 different Bluetooth beacons, pictures showing the 2-DWhen and the 3-D BBUNS views applicationof the route recognizedto be display theed 30 on different the mobile Bluetooth device beacons, screen were pictures downloaded showing the 2-D and 3-D views of the route to be displayed on the mobile device screen were downloaded fromthe 2-D the and web 3-D server views and of thestored route in tothe be databases displayed of on the the mobile mobile devices. device screenThe route were pictures downloaded were from the web server and stored in the databases of the mobile devices. The route pictures were composedfrom the web of 29 server pictures and in stored 2-D and in 29 the pictures databases in 3-D of thethat mobile displayed devices. the crushing The route plant–workplace pictures were composed of 29 pictures in 2-D and 29 pictures in 3-D that displayed the crushing plant–workplace routecomposed and 29 of 29pictures pictures in in2-D 2-D and and 29 29 pictures pictures in in 3-D 3-D that that displayed displayed the the workplace–crushing crushing plant–workplace plant route and 29 pictures in 2-D and 29 pictures in 3-D that displayed the workplace–crushing plant route.route andFigure 29 pictures8 shows in two 2-D arbitrary and 29 pictures pictures in that 3-D were that displayed extracted thefrom workplace–crushing a total of 116 pictures plant in route. 2-D route. Figure 8 shows two arbitrary pictures that were extracted from a total of 116 pictures in 2-D andFigure 3-D.8 shows They twowere arbitrary displayed pictures on the that mobile were extracted device screens from a totalwhen of the 116 BBUNS pictures inrecognized 2-D and 3-D.the and 3-D. They were displayed on the mobile device screens when the BBUNS recognized the BluetoothThey were beacon displayed with on minor the mobile ID 3. device screens when the BBUNS recognized the Bluetooth beacon Bluetoothwith minor beacon ID 3. with minor ID 3.

(a) (b) (a) (b) Figure 8. Screenshots of BBUNS application when the signal of a Bluetooth beacon with minor ID 3 is Figure 8. Screenshots of BBUNS application when the signal of a Bluetooth beacon with minor ID 3 is recognized.Figure 8. Screenshots (a) Two-dimensional of BBUNS application view of the when optimal the signalhaul road of a Bluetoothshowing the beacon current with location minor IDof the 3 is recognized. (a) Two-dimensional view of the optimal haul road showing the current location of the dumprecognized. truck, ( athe) Two-dimensional travel direction, view and of Bl theuetooth optimal beacons haul road installed showing along the currentthe path; location (b) Three- of the dump truck, the travel direction, and Bluetooth beacons installed along the path; (b) Three- dimensionaldump truck, theview travel of the direction, optimal andhaul Bluetooth road. beacons installed along the path; (b) Three-dimensional dimensionalview of the optimal view of haul the optimal road. haul road. Four researchers boarded four dump trucks that were performing haul operations in the Four researchers boarded four dump trucks that were performing haul operations in the underground mine and tested the BBUNS application for three round trips. A Samsung Galaxy S5 underground mine and tested the BBUNS application for three round trips. A Samsung Galaxy S5

Minerals 2017, 7, 228 11 of 16

Four researchers boarded four dump trucks that were performing haul operations in the underground mine and tested the BBUNS application for three round trips. A Samsung Galaxy S5 smartphone,Minerals 2017, 7 Samsung, 228 Galaxy S6 smartphone, Samsung Galaxy S7 smartphone, and Lenovo11 of 16 TAB were used in the application test. These devices were equipped with Bluetooth 4.0 technology or smartphone, Samsung Galaxy S6 smartphone, Samsung Galaxy S7 smartphone, and Lenovo TAB higher. Detailed speciﬁcations for the mobile devices are listed in Table3. Figure9 shows photographs were used in the application test. These devices were equipped with Bluetooth 4.0 technology or of thehigher. mobile Detailed devices wherespecifications the location for the of themobile dump devices trucks are in thelisted underground in Table 3. mineFigure and 9 theshows optimal haulphotographs road were visualized. of the mobile The devices BBUNS where application the location was of ablethe dump to recognize trucks in the the Bluetoothunderground beacons mine that wereand installed the optimal outside haul the road underground were visualized. mine as The well BBUNS as those application installed was inside able the to underground recognize the mine. In addition,Bluetooth whenever beacons that a Bluetoothwere installed beacon outside with the aunderground different minor mine as ID well was as recognized, those installed the inside 2-D and 3-D routethe underground pictures corresponding mine. In addition, to the whenever installation a Bluetooth location beacon of the with beacon a different were minor displayed ID was on the mobilerecognized, device. the 2-D and 3-D route pictures corresponding to the installation location of the beacon were displayed on the mobile device. Table 3. Speciﬁcations of mobile devices used for testing the BBUNS application. Table 3. Specifications of mobile devices used for testing the BBUNS application.

ModelModel GalaxyGalaxy S5 S5 GalaxyGalaxy S6 S6 GalaxyGalaxy S7 S7 LenovoLenovo TAB TAB Properties Properties (SM-G900)(SM-G900) (SM-G920)(SM-G920) (SM-G930)(SM-G930) (S850F)(S850F) AndroidAndroid 6.0 6.0 AndroidAndroid 7.0 7.0 AndroidAndroid 7.0 7.0 AndroidAndroid 4.4.2 4.4.2 OperatingOperating system system (Google,(Google, Menlo Menlo (Google,(Google, Menlo Menlo (Google,(Google, Menlo Menlo (Google,(Google, Menlo Menlo Park,Park, CA, CA, USA) USA) Park,Park, CA, CA, USA) USA) Park,Park, CA, CA, USA) USA) Park,Park, CA, CA, USA) USA) QualcommQualcomm ExynosExynos 7420 7420 Octa Octa ExynosExynos 8890 8890 Octa Octa IntelIntel Atom Atom Z3745 Z3745 SnapdragonSnapdragon 801 801 (Samsung(Samsung (Samsung(Samsung AndroidAndroid processor processor (Intel,(Intel, Santa Santa Clara, Clara, (Qualcomm,(Qualcomm, San San Electronics,Electronics, Suwon, Electronics,Electronics, Suwon, CA,CA, USA) USA) Diego,Diego, CA, CA, USA) USA) Suwon,Korea) Korea) Suwon,Korea) Korea) BluetoothBluetooth BluetoothBluetooth 4.0 4.0 Bluetooth Bluetooth 4.1 4.1 Bluetooth Bluetooth 4.2 4.2 Bluetooth Bluetooth 4.0 4.0 RAMRAM 22 GB GB 3 3GB GB 4 GB 4 GB 2 GB 2 GB Battery 2800 mAh 2550 mAh 3000 mAh 4290 mAh Battery 2800 mAh 2550 mAh 3000 mAh 4290 mAh

(a) (b)

Figure 9. Results of testing the BBUNS application during the haulage operation when (a) leaving the Figure 9. Results of testing the BBUNS application during the haulage operation when (a) leaving the crushing plant, (b) driving toward the 540 ML workplace, (c) passing by the portal of the crushing plant, (b) driving toward the 540 ML workplace, (c) passing by the portal of the underground underground mine, and (d) returning to the crushing plant. mine, and (d) returning to the crushing plant.

Minerals 2017, 7, 228 12 of 16

The time spent in the haul operation was analyzed using the recorded data for the times when the Bluetooth beacons were recognized. It was assumed that the final time when a Bluetooth beacon was recognized was the time halfway between the time when the dump truck first entered the Bluetooth beacon signal reception area (i.e., the time when the Bluetooth beacon was first recognized) and the time when the truck exited the area (i.e., the time when the Bluetooth beacon was last recognized). Table4 lists the times when Bluetooth beacons were recognized for one haul operation among a total of 12 haul operations. Twelve Bluetooth beacons out of 30 installed along the haul road were selected and displayed. It took approximately 8 min and 25 s for the dump truck to leave the crushing plant and reach the underground mine entrance, and approximately 9 min and 25 s to reach the workplace from the underground mine entrance. The dump truck remained at the workplace for approximately 4 min and 8 s for the loading operation. After loading, the dump truck traveled from the workplace to the underground mine entrance for approximately 13 min and 12 s. Traveling to the crushing area required approximately 5 min and 42 s. Therefore, the total time spent for one ore haul operation was approximately 40 min and 52 s.

Table 4. Time data recorded when Bluetooth beacons were recognized on the BBUNS mobile app during one cycle of haulage operations. In the location part of the table, C denotes the crushing plant, H denotes the haul road outside the underground mine, P denotes the portal, A denotes the adit, D denotes the decline, L denotes the level, and W denotes the workplace.

Route 1—Crushing Plant to Workplace Route 2—Workplace to Crushing Plant Beacon Minor ID Location Measured Time Beacon Minor ID Location Measured Time 2 C 09:21:54 a.m. 30 W 09:43:52 a.m. 3 H 09:26:29 a.m. 28 L 09:46:01 a.m. 4 H 09:28:16 a.m. 26 D 09:46:52 a.m. 5 P 09:30:19 a.m. 24 D 09:47:42 a.m. 10 A 09:33:36 a.m. 22 A 09:48:56 a.m. 14 A 09:34:33 a.m. 18 A 09:50:59 a.m. 18 A 09:35:34 a.m. 14 A 09:52:54 a.m. 22 A 09:36:38 a.m. 10 A 09:54:33 a.m. 24 D 09:37:16 a.m. 5 P 09:57:04 a.m. 26 D 09:37:53 a.m. 4 H 09:58:20 a.m. 28 L 09:38:31 a.m. 3 H 10:00:18 a.m. 30 W 09:39:44 a.m. 2 C 10:02:46 a.m. Total travel time 00:40:52

The dump truck travel time information that was analyzed in this study can be used as input data for underground mine fleet management systems, such as Maptek’s MineSuite Fleet management system (2017, Denver, CO, USA) [51], Hexagon Mining’s Jigsaw operations suite (2017, Brisbane, QLD, Australia) [55], Caterpillar’s MineStar (2017, Peoria, IL, USA) [56], and Modular Mining Systems’ Dispatch (2017, Tucson, AZ, USA) [44]. Furthermore, the information can be used in underground mine scheduling systems to identify optimal haul operation scenarios. When the information is used in such systems, the efficiency of haul operations using dump trucks in underground mines can be improved, and the productivity in mines can be increased. The Bluetooth beacon-based underground navigation system designed in this study is limited by delays when visualizing the current location of the dump truck and the optimal haul road to the destination in the underground mine. For example, after the BBUNS application recognizes the signal from a Bluetooth beacon that is installed in the underground mine, there is a delay of several seconds before it recognizes the signal from the next Bluetooth beacon installed at the following location along the haul route. At this time, because the navigation functions recognize that the dump truck is remaining in the same location in the underground mine, it shows a static dump truck location and 2-D and 3-D view of the optimal haul road on the smart device during these few seconds. To overcome this limitation and to visualize the optimal haul road to the destination in real time, it is necessary to install more Bluetooth beacons at shorter intervals. Therefore, this work needs to be expanded as Minerals 2017, 7, 228 13 of 16 follows: (a) designing an optimal installation interval for a sufficient number of Bluetooth beacons in the underground mine, and (b) improving the BBUNS application for signal recognition delay time processing.

4. Conclusions In this study, a Bluetooth beacon-based underground navigation system was designed for use in an underground limestone mine. The results of its field application are presented in this paper. For the field application, a 3-D GIS database was constructed for all of the haul roads in the underground mine, and 50 Bluetooth beacons were installed throughout the mine. An Android-based BBUNS application was developed that recognizes the signals that were transmitted by the Bluetooth beacons and displays the current location of each dump truck, as well as the travel route to the destination, on mobile devices. As a result of the application of the underground mine navigation system to the 540 ML loading point, it was confirmed that a dump truck driver could receive current location information and information on the optimal haul road through a mobile device whenever Bluetooth beacon signals were received by the BBUNS app. In addition, the travel time of the dump truck during the haul operation could be analyzed using time data for when the Bluetooth beacon signals were recognized. The underground mine navigation system has the following advantages. As this system uses Android-based mobile devices to implement navigation functions, it is not necessary to manufacture separate terminals. In addition, the system installation cost is lower than other wireless sensor systems because there is no need to install a separate power network or communication network in the underground mine and because the Bluetooth beacons are inexpensive. Furthermore, the BBUNS application can be extended by implementing additional functions, such as real-time transport equipment location tracking, automatic attendance management, communication between administrators and workers, and navigation functions developed using the Bluetooth beacon SDK. A navigation system for optimal ore haul operations in underground limestone mines was designed in this study. When waste stone is loaded instead of ore at the loading point, however, the loader operator frequently instructs the dump truck driver to haul the waste stone to a waste dump inside the underground mine. For such cases, it is necessary to develop a new routing method that can update the route information anywhere in the underground mine and exchange the acquired data with a receiver outside the mine. Therefore, further studies are required to implement effective navigation functions for haul operations performed inside underground mines.

Acknowledgments: This work was supported by (1) Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2015R1D1A1A01061290), (2) Korea Energy and Mineral Resources Engineering Program funded by the Ministry of Trade, Industry and Energy, and (3) Basic Research Project of the Korea Institute of Geoscience and Mineral resources (KIGAM) funded by the Ministry of Science, ICT and Future Planning of Korea. Author Contributions: Yosoon Choi conceived and designed the application; Sangho Lee and Jieun Baek developed the application; Jangwon Suh and Chaeyoung Lee performed the experiments; Jieun Baek analyzed the data; Yosoon Choi contributed reagents/materials/analysis tools; and Jieun Baek, Jangwon Suh, and Yosoon Choi wrote the paper. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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